camembert v2

train.py

@@ -17,10 +17,10 @@ class MyCamembertForSequenceClassification(torch.nn.Module):
         super(MyCamembertForSequenceClassification, self).__init__()
         self.camembert = CamembertModel.from_pretrained("camembert-base")
 
-        self.l1 = nn.Linear(768, 768 / 2, bias=True)
+        self.l1 = torch.nn.Linear(768, 768 / 2, bias=True)
         self.l1_activation_fun = parse_activation_function("gelu")
 
-        self.l2 = nn.Linear(768/2, num_labels, bias=True)
+        self.l2 = torch.nn.Linear(768/2, num_labels, bias=True)
         self.l2_activation_fun = parse_activation_function("none")
 
     def forward(self, input, attention_mask=None):
@@ -1768,7 +1768,7 @@ if __name__ == "__main__":
     cam_t1_parser.add_argument("--epochs-between-save", default=10, type=int)
     cam_t1_parser.add_argument("--show-progress", default=50, type=int)
     cam_t1_parser.add_argument("--sample", action="store_true")
-    cam_t1_parser.set_defaults(func=finetune_t1_camembert)
+    cam_t1_parser.set_defaults(func=finetune_t1_camembert_v2)
 
     cam_t2_parser = subparsers.add_parser("camembert-t2-v2")
     cam_t2_parser.add_argument("train")